Internet of Things (IoT) Training in Slovakia

This instructor-led, live training in Slovakia (online or onsite) targets advanced-level IoT developers and smart home enthusiasts looking to automate IoT processes and build innovative solutions using n8n.

By the end of this training, participants will be able to:

• Set up and configure n8n for IoT workflow automation.
• Integrate IoT devices and platforms using n8n nodes and connectors.
• Implement custom workflows to automate IoT tasks and processes.
• Use IoT protocols like MQTT and REST APIs within n8n workflows.
• Monitor, troubleshoot, and optimize IoT automation workflows.

As the next-generation standard for wireless communication, 6G is poised to revolutionize IoT ecosystems by delivering ultra-fast connectivity, advanced sensing capabilities, and seamlessly integrated AI functions.

This instructor-led live training, available both online and onsite, is designed for advanced professionals seeking to understand and capitalize on the emerging convergence of 6G technologies and IoT applications.

Upon completing this course, learners will be equipped to:

• Articulate the fundamental technical concepts underlying 6G.
• Evaluate how 6G will transform IoT device communication and architectural frameworks.
• Analyze 6G-enabled IoT use cases across various industries.
• Develop strategies for integrating 6G capabilities into current IoT solutions.

Course Format

• Concept-driven lectures paired with expert-led discussions.
• Practical exercises designed to reinforce core engineering principles.
• Guided exploration of case studies and scenario analyses.

Customization Options

• For customized training versions aligned with your organization's technology roadmap, please contact us to arrange a session.

This instructor-led, live training in Slovakia (online or onsite) is aimed at intermediate-level professionals who wish to apply Federated Learning to optimize IoT and edge computing solutions.

By the end of this training, participants will be able to:

• Understand the principles and benefits of Federated Learning in IoT and edge computing.
• Implement Federated Learning models on IoT devices for decentralized AI processing.
• Reduce latency and improve real-time decision-making in edge computing environments.
• Address challenges related to data privacy and network constraints in IoT systems.

This instructor-led, live training in Slovakia (online or onsite) is aimed at intermediate-level developers, system architects, and industry professionals who wish to leverage Edge AI for enhancing IoT applications with intelligent data processing and analytics capabilities.

By the end of this training, participants will be able to:

• Understand the fundamentals of Edge AI and its application in IoT.
• Set up and configure Edge AI environments for IoT devices.
• Develop and deploy AI models on edge devices for IoT applications.
• Implement real-time data processing and decision-making in IoT systems.
• Integrate Edge AI with various IoT protocols and platforms.
• Address ethical considerations and best practices in Edge AI for IoT.

This instructor-led, live training in Slovakia (online or onsite) is aimed at intermediate-level IoT developers, embedded engineers, and AI practitioners who wish to implement TinyML for predictive maintenance, anomaly detection, and smart sensor applications.

By the end of this training, participants will be able to:

• Understand the fundamentals of TinyML and its applications in IoT.
• Set up a TinyML development environment for IoT projects.
• Develop and deploy ML models on low-power microcontrollers.
• Implement predictive maintenance and anomaly detection using TinyML.
• Optimize TinyML models for efficient power and memory usage.

This instructor-led, live training in Slovakia (online or onsite) is designed for intermediate IT professionals and business managers who want to understand how IoT and edge computing can drive efficiency, real-time processing, and innovation across various industries.

By the end of this training, participants will be able to:

• Understand the principles of IoT and edge computing and their role in digital transformation.
• Identify use cases for IoT and edge computing in manufacturing, logistics, and energy sectors.
• Differentiate between edge and cloud computing architectures and deployment scenarios.
• Implement edge computing solutions for predictive maintenance and real-time decision-making.

Embedded systems are specialized computing solutions engineered to execute specific tasks within broader systems. The Internet of Things (IoT) refers to a network of physical devices equipped with sensors and software, enabling them to communicate and share data via the internet.

This instructor-led live training, available either online or on-site, targets technical professionals at the beginner level who aim to grasp and apply concepts related to embedded systems and IoT using C programming and microcontroller architectures.

Upon completion of this training, participants will be able to:

• Grasp the architecture and key components of embedded systems.
• Write and compile C code to facilitate interaction with embedded hardware.
• Utilize microcontroller peripherals, including timers and Analog-to-Digital Converters (ADCs).
• Comprehend the role of embedded systems within IoT architectures.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical sessions.
• Hands-on implementation within a live laboratory environment.

Options for Course Customization

• For inquiries regarding customized training for this course, please reach out to us to make arrangements.

The objective of this training is to provide an introduction to the realms of the Internet of Things (smart solutions) and blockchain technology, highlighting the benefits and drawbacks associated with these technological domains.

The objective of this training is to clarify the nature of 5G networks and their influence on smart technologies. The course aims to present both the advantages and disadvantages of the relationship between these technologies (5G and IoT), while highlighting the developmental directions of a network designed from the outset for the smart world.

The objective of the training is to explain what constitutes Smart Solutions (Internet of Things, AI, Blockchain, Virtual Reality, Metaverse) and what does not, while highlighting the advantages and disadvantages of these technological landscapes.

Technological advancements and the exponential growth of information are reshaping business operations across various sectors, including government. The volume of data generated by government entities and the rate of digital archiving are increasing rapidly, driven by the proliferation of mobile devices and applications, smart sensors, cloud computing solutions, and citizen-facing portals. As digital information expands in complexity, managing, processing, storing, securing, and disposing of it becomes increasingly challenging. New tools for capturing, searching, discovering, and analyzing data are enabling organizations to derive valuable insights from unstructured data. The government sector is at a critical juncture, recognizing information as a strategic asset. Agencies must now protect, leverage, and analyze both structured and unstructured information to better serve the public and meet mission objectives. As government leaders work to transform their organizations into data-driven entities, they are establishing the framework to correlate dependencies across events, people, processes, and information.

High-impact government solutions are emerging from the integration of several disruptive technologies:

• Mobile devices and applications
• Cloud services
• Social business technologies and networking
• Big Data and analytics

Big Data represents a transformative industry solution that enables governments to make better decisions by acting on patterns identified through the analysis of vast volumes of data—whether related or unrelated, structured or unstructured.

However, achieving these results requires more than just collecting large amounts of data. "Making sense of these volumes of Big Data requires cutting-edge tools and technologies that can analyze and extract useful knowledge from vast and diverse streams of information," noted Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy in a post on the OSTP Blog.

The White House took significant steps to assist agencies in identifying these technologies by launching the National Big Data Research and Development Initiative in 2012. This initiative allocated over $200 million to maximize the potential of the Big Data explosion and the necessary analytical tools.

The challenges presented by Big Data are as formidable as its promise is encouraging. Efficiently storing data is one such challenge. With budgets always under pressure, agencies must minimize storage costs per megabyte while ensuring data remains easily accessible so users can retrieve it whenever and however they need it. Backing up massive data volumes further complicates this task.

Effective data analysis poses another major challenge. Many agencies utilize commercial tools to sift through vast amounts of data, identifying trends that enhance operational efficiency. (A recent MeriTalk study found that federal IT executives believe Big Data could help agencies save over $500 billion while fulfilling mission objectives.)

Custom-developed Big Data tools are also enabling agencies to address their analytical needs. For instance, the Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other agencies. This system has helped medical researchers identify links that alert doctors to aortic aneurysms before they occur. It is also used for routine tasks, such as screening resumes to match job candidates with hiring managers.

Insurtech (also known as Digital Insurance) represents the intersection of insurance and emerging technologies. Within the Insurtech landscape, "digital insurers" leverage technological innovations to transform their business and operational models, aiming to lower costs, enhance customer experiences, and increase operational agility.

This instructor-led training helps participants understand the technologies, methodologies, and mindset required to drive digital transformation within their organizations and across the wider industry. The course is designed for managers who need a comprehensive overview, wish to cut through hype and jargon, and are ready to take initial steps toward building an Insurtech strategy.

Upon completion of this training, participants will be able to:

• Discuss Insurtech and its various components with intelligence and systematic clarity
• Identify and clarify the role of each key technology in the Insurtech ecosystem
• Develop a general strategy for implementing Insurtech within their organization

Audience

• Insurance professionals
• Technologists working within the insurance industry
• Stakeholders in the insurance sector
• Consultants and business analysts

Course Format

• A mix of lectures, discussions, exercises, and group case study activities

This instructor-led, live training in Slovakia (online or onsite) is aimed at product managers and developers who wish to use Edge Computing to decentralize data management for faster performance, leveraging smart devices located on the source network.

By the end of this training, participants will be able to:

• Understand the basic concepts and advantages of Edge Computing.
• Identify the use cases and examples where Edge Computing can be applied.
• Design and build Edge Computing solutions for faster data processing and reduced operational costs.

This instructor-led, live training in Slovakia (onsite or remote) is designed for engineers who wish to set up, deploy, and manage secure IoT applications.

By the end of this training, participants will be able to:

• Develop and deploy applications for secure IoT device management.
• Securely integrate IoT devices into the Cloud.
• Integrate IoT applications with existing infrastructure.

The Internet of Things (IoT) represents an emerging technological domain that facilitates the wireless connectivity between physical objects and software applications, enabling remote sensing and control. Augmented Reality (AR) enhances user experiences by integrating virtual, computer-generated elements into the physical real-world environment, allowing businesses to deliver real-time, contextual information to users. Both technologies are experiencing rapid adoption rates across various industries.

During this instructor-led live training, participants will gain a solid understanding of IoT and AR fundamentals and learn how to apply these concepts to their organization's operations and strategic planning.

Upon completion of this training, participants will be able to:

• Grasp the core principles of IoT and AR
• Comprehend the operational mechanisms of IoT and AR technologies
• Identify strategies for integrating IoT and AR into business objectives
• Make informed, data-driven business decisions regarding IoT and AR implementation

Target Audience

• Managers
• Entrepreneurs

Course Format

• A blend of lectures, discussions, exercises, and extensive hands-on practice

Important Note

• For customized training options, please contact us to arrange a session tailored to your needs.

In this instructor-led live training in Slovakia, participants will explore the fundamentals of IoT by developing an Arduino-based IoT sensor system step-by-step.

By the end of this training, participants will be able to:

• Understand IoT principles, including its components and communication techniques.
• Learn how to use Arduino communication modules suitable for various IoT systems.
• Learn how to use and program a mobile application to control Arduino.
• Use a Wi-Fi module to connect the Arduino to another device.
• Build and deploy their own IoT Sensor System.

The Internet of Things (IoT) represents a network infrastructure that wirelessly connects physical devices with software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture mechanisms. Azure provides a robust suite of cloud services that includes an IoT Suite with preconfigured solutions designed to help developers accelerate the creation of IoT projects.

In this instructor-led live training, participants will gain the skills needed to develop IoT applications using Azure.

Upon completion of this training, participants will be able to:

• Grasp the fundamental concepts of IoT architecture
• Install and configure the Azure IoT Suite
• Identify the advantages of leveraging Azure for programming IoT systems
• Implement key Azure IoT services, including IoT Hub, Functions, Stream Analytics, Power BI, Cosmos DB, DocumentDB, and IoT Device Management
• Build, test, deploy, and troubleshoot IoT systems using Azure

Audience

• Developers
• Engineers

Format of the course

• A blend of lectures, discussions, exercises, and extensive hands-on practice

Note

• To request customized training for this course, please contact us to arrange it.

The Internet of Things (IoT) refers to a network infrastructure that wirelessly connects physical devices with software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. C is a general-purpose programming language recommended for IoT development due to its widespread use and benefits in low-level programming.

In this instructor-led live training, participants will learn how to develop IoT solutions using C.

By the end of the training, participants will be able to:

• Install and configure NetBeans for programming IoT systems with C
• Grasp the fundamentals of IoT architecture
• Understand the advantages of using C for IoT programming
• Build, test, deploy, and troubleshoot an IoT system using C

Audience

• Developers
• Engineers

Course Format

• A blend of lectures, discussions, exercises, and extensive hands-on practice

Note

• To request customized training for this course, please contact us to arrange it.

Unlike other technologies, the Internet of Things (IoT) is significantly more complex, spanning nearly every branch of core engineering including Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each engineering layer involves aspects of economics, standards, regulations, and the evolving state of the art. For the first time, a modest course is offered to cover all these critical aspects of IoT Engineering.

Summary

An advanced training program covering the current state of the art in the Internet of Things.

Cuts across multiple technology domains to develop awareness of an IoT system, its components, and how it can help businesses and organizations.

Live demo of model IoT applications to showcase practical IoT deployments across different industry domains, such as Industrial IoT, Smart Cities, Retail, Travel & Transportation, and use cases around connected devices & things.

Target Audience

Managers responsible for business and operational processes within their respective organizations who want to know how to harness IoT to make their systems and processes more efficient.

Entrepreneurs and Investors who are looking to build new ventures and want to develop a better understanding of the IoT technology landscape to see how they can leverage it in an effective manner.

Estimates for the Internet of Things (IoT) market value are massive, since by definition, IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The IoT will account for an increasingly huge number of connections: 1.9 billion devices today, and 9 billion by 2018. That year, it will be roughly equal to the number of smartphones, smart TVs, tablets, wearable computers, and PCs combined.

In the consumer space, many products and services have already crossed over into the IoT, including kitchen and home appliances, parking, RFID, lighting and heating products, and a number of applications in the Industrial Internet.

However, the underlying technologies of IoT are nothing new, as M2M communication has existed since the birth of the Internet. What changed in the last couple of years is the emergence of numerous inexpensive wireless technologies added by the overwhelming adoption of smartphones and tablets in every home. The explosive growth of mobile devices led to the present demand for IoT.

Due to unbounded opportunities in the IoT business, a large number of small and medium-sized entrepreneurs jumped on the bandwagon of the IoT gold rush. Also, due to the emergence of open-source electronics and IoT platforms, the cost of developing an IoT system and further managing its sizable production is increasingly affordable. Existing electronic product owners are experiencing pressure to integrate their devices with the Internet or mobile apps.

This training is intended for a technology and business review of an emerging industry so that IoT enthusiasts/entrepreneurs can grasp the basics of IoT technology and business.

Course Objective

Main objective of the course is to introduce emerging technological options, platforms, and case studies of IoT implementation in home & city automation (smart homes and cities), Industrial Internet, healthcare, government, mobile cellular, and other areas.

Basic introduction of all the elements of IoT: Mechanical, Electronics/sensor platform, Wireless and wireline protocols, Mobile to Electronics integration, Mobile to enterprise integration, Data-analytics, and Total control plane.

M2M Wireless protocols for IoT: WiFi, Zigbee/Zwave, Bluetooth, ANT+: When and where to use which one?

Mobile/Desktop/Web app for registration, data acquisition, and control – Available M2M data acquisition platforms for IoT: Xively, Omega, and NovoTech, etc.

Security issues and security solutions for IoT.

Open source/commercial electronics platforms for IoT: Raspberry Pi, Arduino, ArmMbedLPC, etc.

Open source/commercial enterprise cloud platforms for AWS-IoT apps, Azure-IoT, Watson-IoT cloud, in addition to other minor IoT clouds.

Studies of the business and technology of some common IoT devices like Home automation, Smoke alarms, vehicles, military, home health, etc.

The Internet of Things (IoT) represents a network infrastructure that wirelessly connects physical objects with software applications, enabling seamless communication, data exchange, and integration through network communications, cloud computing, and data capture mechanisms. Java, renowned for its "write once, run anywhere" capability, is a versatile language recommended for IoT development due to its high portability and efficiency.

This instructor-led live training will guide participants in developing IoT solutions using Java.

Upon completion of this course, participants will be able to:

• Install and configure necessary tools and frameworks, such as the Eclipse Open IoT Stack, for Java-based IoT programming
• Comprehend the core principles of IoT architecture
• Utilize the Eclipse Open IoT Stack for Java to connect and manage devices within an IoT environment
• Construct, test, and deploy IoT systems using Java

Target Audience

• Software Developers
• Engineers

Course Format

• A blend of lectures, discussions, exercises, and extensive hands-on practice

Note

• For customized training options, please reach out to us to arrange a tailored session.

In contrast to other technologies, IoT is significantly more complex, spanning nearly every core engineering discipline: Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. Each engineering layer involves considerations of economics, standards, regulations, and the evolving state of the art. For the first time, this modest course covers all these critical aspects of IoT Engineering.

For manufacturing professionals, the most critical aspect is understanding advancements in the Industrial Internet of Things. This includes predictive and preventative maintenance, condition-based monitoring of machines, production and energy optimization, supply-chain optimization, and uptime of manufacturing utilities, among other factors.

Summary

• An advanced training program covering the current state of the art in the Internet of Things within Smart Factories.
• Cross-referencing multiple technology domains to develop awareness of IoT systems, their components, and how they can benefit manufacturing managerial professionals.
• Live demonstration of model IIoT applications for smart factories.

Target Audience

• Managers responsible for business and operational processes within their respective manufacturing organizations who wish to learn how to leverage IoT to enhance the efficiency of their systems and processes.

Duration 3 Days (8 hours per day)

Estimates for the Internet of Things (IoT) market value are massive. By definition, IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The number of IoT connections is increasing rapidly: from 1.9 billion devices today to an estimated 9 billion by 2018. In that year, the number of connected devices will roughly equal the combined total of smartphones, smart TVs, tablets, wearable computers, and PCs.

In the consumer space, many products and services have already transitioned into the IoT ecosystem, including kitchen and home appliances, parking systems, RFID, lighting, heating products, and various applications within the Industrial Internet.

While the underlying technologies of IoT are not new—Machine-to-Machine (M2M) communication has existed since the birth of the Internet—what has changed in recent years is the emergence of numerous inexpensive wireless technologies. This change is driven by the widespread adoption of smartphones and tablets in every home. The explosive growth of mobile devices has led to the current demand for IoT solutions.

Industrial IoT (IIoT) for manufacturing has been in wide use since 2014, with a large number of IIoT innovations occurring since then. This course will introduce all the important aspects of these innovations in the IIoT field.

This training is intended as a technology and business review of this emerging industry, allowing IoT enthusiasts and entrepreneurs to grasp the basics of IoT technology and business models.

Course Objective

The main objective of the course is to introduce emerging technological options, platforms, and case studies of IoT implementation in smart factories for the manufacturing sector.

1. Studies of the business and technology of common IIoT platforms like Siemens MindSphere and Azure IoT.
2. Open-source and commercial enterprise cloud platforms for AWS IoT, Azure IoT, Watson IoT, MindSphere IIoT cloud, in addition to other minor IoT clouds.
3. Open-source and commercial electronics platforms for IoT: Raspberry Pi, Arduino, ARM MbedLPC, etc.
4. Security issues and security solutions for IIoT.
5. Mobile/Desktop/Web apps for registration, data acquisition, and control.
6. M2M Wireless protocols for IoT: WiFi, LoRa, BLE, Ethernet, EtherCAT, PLC: When and where to use each?
7. Basic introduction to all IoT elements: Mechanical, Electronics/Sensor platform, Wireless and wireline protocols, Mobile-to-Electronics integration, Mobile-to-enterprise integration, Data analytics, and the Total control plane.

The Internet of Things (IoT) represents a network infrastructure that wirelessly connects physical objects with software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture.

Blockchain is a decentralized database system that stores data in ledgers distributed across numerous nodes.

Integrating blockchain technology with IoT enables the accessibility and supply of IoT data without requiring central control. This integration unlocks a range of new possibilities and offers multiple benefits for business organizations.

In this instructor-led, live remote training, participants will learn how blockchain and IoT can collaborate by working through a series of hands-on, live-lab exercises.

By the end of this training, participants will be able to:

• Understand how blockchain and IoT can work together to provide solutions for their organization
• Explore various tools and resources to implement a blockchain-based IoT solution for their organization

Audience

• Developers
• Managers

Format of the Course

• A mix of lectures, discussions, exercises, and extensive hands-on practice.

Note

• To request customized training for this course, please contact us to arrange.

Connected devices are disrupting numerous industries, with the power utility sector being no exception. Power utility companies currently face four primary challenges stemming from the proliferation of IoT:

1. Vendors are increasingly connecting machines, controllers, HMIs, and SCADA systems to the cloud, promising enhanced analytics and insights for predictive and preventative maintenance. However, stringent quarantine policies governing critical assets prevent power companies from leveraging these new IoT features offered by machine and controller vendors.
2. As the cost of solar and wind microgrids continues to decline, utility companies anticipate a drop in revenue from traditional power generation. To offset this, they must aggressively pursue new revenue streams, such as Energy Management as a Service, Energy Storage as a Service, and grid services for EV charging and peer-to-peer (P2P) energy trading among homes, microgrids, and batteries. These transactions require smart metering, smart grids, and secure exchanges facilitated by Distributed Ledger Technology (DLT) like IOTA. Additionally, utilities are exploring the provision of smart city services to municipal authorities.
3. For critical infrastructure such as dams, ICOLD (International Committee of Large Dams) mandates real-time Structural Health Monitoring (SHM) to detect impending risks of collapse in dams, rock formations, or tunnels. This allows for the early evacuation of people in affected areas.
4. Another emerging revenue area is EV charging in parking facilities, raising the question of how IoT can facilitate smart charging and parking solutions.

Over the past three years, IoT engineering has undergone significant transformations, largely driven by Microsoft, Google, and Amazon. These tech giants have invested billions to develop IoT platforms that are easier to manage and secure. IoT edge computing has gained substantial momentum as the primary method for practical IoT implementation, while 5G promises to further revolutionize the IoT business landscape. This has led to unprecedented funding in IoT research. Consequently, it is essential for practicing engineers to understand the IoT platforms developed for major players like AWS, Google, and especially Microsoft.

However, none of these platforms offer a fully comprehensive solution for scalable IoT. Deploying smart meters to millions of homes requires additional technologies for securing the meters, radio networks, IoT management systems, and other secure services. Strategy, pricing, and security in any IoT deployment must be optimized and acceptable. Given the interdisciplinary nature of this knowledge, it is challenging for any single company to assemble a team capable of meeting all requirements.

This course makes a concerted effort to educate key decision-makers, developers, and security experts on the challenges, risks, and practical approaches to deploying IoT for next-generation power utility businesses.

Furthermore, as IoT deployments scale, managing services for thousands of sensors and connections has emerged as a distinct engineering research subject. This area, formerly known as managed IoT services, is experiencing rapid growth because the challenges of scalable IoT management are greater than the implementation itself. This includes securing over-the-top firmware/software updates, managing sensor and system calibration, auto-diagnosing connection issues, identifying root causes of API failures, and tracking the health of hardware and services in distributed systems.

Course Objectives

The main objective of this course is to introduce emerging technological options, platforms, and case studies of IoT implementation in power utility companies, focusing on Smart Metering, Smart Cars, SHM (Structural Health Monitoring), Power Quality Diagnosis, and Smart Contracts. It provides a basic introduction to all IoT elements, including mechanical and electronics/sensor platforms, wireless and wireline protocols, mobile-to-electronics integration, mobile-to-enterprise integration, data analytics, and control plane applications.

1. IoT Technology Stacks: Devices, Gateways, Edge, Edge Cloud, Public Cloud, IoT databases, Web & Mobile Applications for IoT, Centralized vs. Decentralized IoT
2. IoT Ecosystem for Business: Third-party device management and risk management of the entire IoT ecosystem
3. M2M Wireless Protocols for IoT: WiFi, SigFox, LoRa, LPWAN, Zigbee/Z-Wave, Bluetooth, ANT+ - Guidelines on when and where to use each
4. Fundamentals of IoT Gateways: Risks, Management, and Ecosystem
5. Mobile/Desktop/Web Apps for registration, data acquisition, and control - Overview of available M2M data acquisition platforms for IoT (AWS IoT, Azure IoT, Google IoT)
6. Security Issues and Solutions for IoT: Review of security across all technology stacks
7. Enterprise IoT Platforms: Microsoft Azure IoT Suites, AWS IoT, Google IoT, Siemens MindSphere
8. Smart Metering Standards: Open Smart Grid Protocols (OSGP), ANSI C2.18 Protocols, NIST Standard for HAN (Home Area Network), HomePlug Powerline Alliance, Smart Meter Security Standard (IEC 62056)
9. Distributed Ledger Technology (DLT): Blockchain, HyperLedger, and DAG (Directed Acyclic Graph) for smart contracts, P2P transactions, and smart car charging
10. IoT for Critical Infrastructure: Dams, Transformers, Substations, High-Tension Wires

The Internet of Things (IoT) serves as a network infrastructure that wirelessly connects physical objects with software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. Python is a high-level programming language recommended for IoT due to its clear syntax and large community support.

In this instructor-led, live training, participants will learn how to program IoT solutions with Python.

By the end of this training, participants will be able to:

• Understand the fundamentals of IoT architecture
• Learn the basics of using Raspberry Pi
• Install and configure Python on Raspberry Pi
• Learn the benefits of using Python in programming IoT systems
• Build, test, deploy, and troubleshoot an IoT system using Python and Raspberry Pi

Audience

• Developers
• Engineers

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Note

• To request a customized training for this course, please contact us to arrange.

The Internet of Things (IoT) represents a network infrastructure that wirelessly connects physical objects with software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture.

In this instructor-led live training, participants will explore the fundamentals of IoT by actively building an IoT sensor system using the Raspberry Pi.

Upon completion of this training, participants will be able to:

• Comprehend IoT principles, including its components and communication methods
• Configure the Raspberry Pi specifically for IoT applications
• Design and deploy their own IoT Sensor System

Audience

• Hobbyists
• Hardware and software engineers and technicians
• Technical professionals across all industries
• Beginner developers

Format of the course

• A combination of lectures, discussions, exercises, and extensive hands-on practice

Note

• The Raspberry Pi is compatible with various operating systems and programming languages. This course utilizes the Linux-based Raspbian operating system and Python as the programming language. If you require a different setup, please contact us to make arrangements.
• Participants are responsible for purchasing their own Raspberry Pi hardware and components.

In the past three years, the engineering landscape for IoT has undergone massive transformations, largely propelled by tech giants like Microsoft, Google, and Amazon. These industry leaders have invested billions into developing IoT platforms designed to make data management and perimeter security more accessible. Simultaneously, IoT edge computing has gained significant momentum in both research and deployment, establishing itself as the primary method for practical IoT implementation. Furthermore, the advent of 5G promises to further revolutionize the IoT business sector, resulting in an unprecedented wave of new research funding areas within the industry.

Despite this progress, large-scale IoT adoption remains slow due to persistent security concerns at multiple levels. Securing firmware and gateways is far from ideal. A major hurdle is the lack of consensus among major IoT vendors regarding security standards. While Microsoft Azure and Amazon AWS have advanced their own proprietary security frameworks, NIST is working towards a more comprehensive universal standard. Although the OWASP model's ten layers of IoT security provided some impact, it failed to gain widespread traction due to non-adoption by major platforms like Azure and Google.

Another significant area of concern is firmware security. Primarily, most firmware remains vulnerable to patching vulnerabilities, whether addressed via OTA (over-the-air) updates or locally through hardware ports.

Course Objective

1. Provide an introduction to technology stacks, data models, and IoT vulnerabilities.
2. Illustrate vulnerability layers at each stack level and between stacks.
3. Analyze vulnerabilities originating from vendors and third-party devices.
4. Educate participants on the NIST standard for IoT security.

In this instructor-led live training in Slovakia, participants will understand Internet of Things (IoT) architectures and learn about different IoT security solutions applicable to their organization.

By the end of this training, participants will be able to:

• Understand IoT architectures.
• Understand emerging IoT security threats and solutions.
• Implement technologies for IoT security in their organization.

This instructor-led, live training in Slovakia (online or onsite) is aimed at developers and programmers who wish to install, configure, and manage the Kaa platform to build IoT applications.

By the end of this training, participants will be able to build, develop, manage, and implement IoT applications for smart devices and machines using Kaa.

Machine-to-Machine (M2M) denotes direct, automated communication between interconnected mechanical or electronic devices.

In this instructor-led, live training in Slovakia, participants will explore the various aspects of NB-IoT (also known as LTE Cat NB1) as they develop and deploy a sample NB-IoT-based application.

Upon completion of this training, participants will be able to:

• Identify the key components of NB-IoT and understand how they integrate to form a cohesive ecosystem.
• Understand and articulate the security features inherent in NB-IoT devices.
• Develop a basic application for tracking NB-IoT devices.

In this instructor-led, live training conducted Slovakia, participants will learn how to maximize the performance of Nginx while setting up, configuring, monitoring, and troubleshooting it for handling various forms of HTTP and TCP traffic. The topics include configuring essential Nginx parameters, as well as optimizing the OS and virtual machine settings to gain maximum value from Nginx.

ThingsBoard is an open-source IoT platform that provides device management, data collection, processing, and visualization for your IoT solution.

In this instructor-led live training, participants will learn how to integrate ThingsBoard into their IoT solutions.

By the end of this training, participants will be able to:

• Install and configure ThingsBoard
• Understand the fundamentals of ThingsBoard features and architecture
• Build IoT applications with ThingsBoard
• Integrate ThingsBoard with Kafka for telemetry device data routing
• Integrate ThingsBoard with Apache Spark for data aggregation from multiple devices

Audience

• Software engineers
• Hardware engineers
• Developers

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Note

• To request a customized training for this course, please contact us to arrange.